Threshold impact for CNN partitioning algorithm in the Versatile Video Coding standard

Versatile Video Coding (VVC) standard was published in July 2020 by the Joint Video Experts Team (JVET). The VVC coding scheme has been enhanced by introducing new coding technologies compared to HEVC codec scheme. The added tools improved the Rate-Distortion (RD) performance while increasing the co...

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Bibliographic Details
Main Authors: Abdallah, Bouthaina, Belghith, Fatma, Ben Ayed, Mohamed Ali, Masmoudi, Nouri
Format: Conference Proceeding
Language:English
Subjects:
bithreshold
complexity
Complexity theory
Convolution Neural Network (CNN)
Encoding
Partitioning algorithms
Prediction algorithms
Quadtree with Nested Multi-Type Tree (QTMT)
Software algorithms
Versatile Video Coding (VVC)
Video coding
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Summary:Versatile Video Coding (VVC) standard was published in July 2020 by the Joint Video Experts Team (JVET). The VVC coding scheme has been enhanced by introducing new coding technologies compared to HEVC codec scheme. The added tools improved the Rate-Distortion (RD) performance while increasing the coding complexity. The Quadtree with Nested Multi-Type Tree (QTMT) partitioning module is one of the most complex improvement. Therefore, we suggested a low complexity QTMT algorithm based on the Convolution Neural Network (CNN). The proposed method adopted bi-threshold values in order to determine the partitioning decision according to the predicted probabilities. In this paper, a study of the bi-threshold values impact on both coding efficiency and complexity reduction is presented using the VVC reference software VTM3.0 in order to develop a method that may automatically select the appropriate bi-threshold value.
ISSN:2474-0446
DOI:10.1109/SSD58187.2023.10411176